A HMM-Based Fuzzy Affective Model For Emotional Speech Synthesis

摘要：

Existing emotional speech synthesis applications usually distinguish between a small number of emotions in speech. However this set of so called basic emotions in speech varies from one application to another depending on their according needs. In order to support such differing application needs an emotional speech fuzzy model is presented. In addition to existing models it supports also the synthesis of derived emotions which are combinations of basic emotions in speech. We show the application of this model by a prosody based Hidden Markov Models (HMM). The approach is based on emotional speech corpus database that trained by HMM. This approach use three kinds of emotional speech corpus (anger, happiness, and sadness) from recordings of a male and a female speaker of Chinese and English. Both the selection of features and the design of the synthesis are addressed.

关键词： Hidden Markov Models(HMM) emotion computing fuzzy emotion hypercube emotional speech synthesis

作者: Yuqiang Qin Xueying Zhang Hui Ying

作者单位: Taiyuan University of Science and Technology Taiyuan University of Technology Taiyuan, China Taiyuan University of Technology Taiyuan, China Taiyuan Normal University Taiyuan, China

会议类型: 国际会议

会议名称: 2010 2nd International Conference on Signal Processing System(2010年信号处理系统国际会议 ICSPS 2010)

会议地点: 大连

会议语种:英文

页码: 2206-2209

在线出版日期: 2010-07-05（万方平台首次上网日期，不代表论文的发表时间）